Echo cancellation using adaptive IIR and FIR filters

ABSTRACT

Disclosed is a method and system adapted to receive an input signal from a far end transmission, to take in a near end return signal, and to inject into the return signal, prior to sending the return to the far end, a corrective signal whereby, for example, echoes in the return signal may be reduced or cancelled. A first exemplary embodiment includes one or more adaptive infinite impulse response (IIR) filters and one or more adaptive finite-impulse response filters (FIR) filters running in parallel each having an output that may be selected as the corrective signal based on filter performance determinations. A second exemplary embodiment includes an adaptive FIR filter outputting the corrective signal where the adaptive FIR filter has selected for it, based on filter performance determinations, an output of one or more adaptive IIR filters or a conditioned return signal selected as a reference.

FIELD OF THE INVENTION

The present invention relates to methods and systems of echocancellation and particularly to method and systems of achieving echocancellation using an adaptive Infinite Impulse Response (IIR) filterand an adaptive Finite-Impulse Response (FIR) filter.

BACKGROUND

In transmission or communication system, signals originating from a farend of a communication circuit are received at a near end of thecircuit. The received signals, either electrically or acoustically, mayfind their way into the return path along with near-end input. Far-endreception of the near-end input may include an attenuated and delayedreflection, i.e., an echo, of the original far-end input signals. Intelephone systems, whether wired or wireless, these echo phenomena canmake a conversation unintelligible. In data communication systems, againwhether wired or wireless, such echoes can cause errors in transmissionor otherwise degrade throughput performance.

Adaptive filters are used in numerous applications to remove undesiredfrequency content from a signal and are used in telecommunicationsystems as echo cancellation systems to remove from a signal echoes thatmay arise as a result of the reflection and/or unwanted coupling ofinput signals back to the originator of the input signals. For example,echoes occur in instances where signals that were emitted from aloudspeaker are then received and retransmitted through a microphone,i.e., acoustic echo, or when reflections of a far-end signal aregenerated in the course of transmission along wiring junctions whereimpedance mismatch occur, i.e., line echo.

Presently, an adaptive finite-impulse response (FIR) filter may be usedto reduce or eliminate the echo where the echo cancellationcharacteristics are defined in the International TelecommunicationUnion-Standardization Sector (ITU-T) Recommendations G.165 and G.168 andthe contents of each of the foregoing ITU Recommendations beingincorporated herein by reference as if set forth in full. FIG. 1illustrates a functional block diagram of an echo cancellation circuit150 interposed between the far end and the near end of atelecommunication system 100 where the echo cancellation circuitoperates at a near end 102. The near-end input 130 to return signal 132is shown as combining with a near-end echo signal 122 represented by thefar-end input signal 110 as filtered by, that is, as attenuated anddelayed by, the z-domain echo transfer function 120, H(z). The resultingreturn signal 132 is represented then as a linear combination of thenear-end input signal 130 and the near-end echo signal 122.

Accordingly, when a digital representation of the echo transfer functionis in the form of an adaptive FIR 156, and the gains are adjusted tomimic the echo transfer function 120, when the far-end input signal 110is filtered by the adaptive FIR 156, the resulting signal 158 may bedifferenced with the return signal 132 to cancel the echo from thereturn line signal 132. As illustrated in FIG. 1, to accomplish thiscanceling effect, the post-cancellation return line signal 140 isdirected into a nonlinear processing module 152 that may pre-filterbackground or ambient noise and establish a threshold above which littleor no adaptation of the IIR filter is permitted. The threshold logic isus used to address the double talk situations where the return signalmay have both near-end input and echo in temporal proximity. If thepre-filtered return line signal is below the threshold, it may be used,at each step k, as an error signal 154, e_(k), to drive the adaptationof the gains the FIR filter 156. The FIR filter may require severaldelay states with each output or input state being tapped, multiplied bya gain and summed. The gains for the FIR filter may be chosen torepresent the most likely echo transfer function 120, H(z), andsubsequently, these gains may be adjusted by relationships driven by theerror signal, e_(k). Least-mean-square (LMS) adaptive algorithms arecommonly implemented in adaptive cancellation devices to adjust thegains of the adaptive FIR filter. A FIR filter may be represented as

$\begin{matrix}{{H_{k}(z)} = {\sum\limits_{n = 0}^{L}{h_{n,k} \cdot z^{- n}}}} & \lbrack 1\rbrack\end{matrix}$

A typical rule of adaptation or adjustment of the FIR filter gains is touse the product of the error signal 154, the normalized input signal,and a step size, or adapting gain, β, to adjust the gains. For example,for each filter coefficient, n, where n=0, 1, 2, . . . L:h _(n,k+1) =h _(n,k) +β*e(k)*x _(k−1) /x _(max).  [2]

FIR filters typically require a long tap delay to model effectively anecho return path. FIR filters, while stable representations of all zerotransfer functions, are typically slow to adapt, require more memorythan recursive filters memory, and, due to the number of taps, can becomputationally cumbersome.

With certain types of input signal, such as human speech, arecharacterized by the dominance of distinct peaks followed by a longdecay over time. A majority of the computation is devoted to FIRcoefficient update on the long decay portion of the signal, whichactually contributed little significance to the actual echo energy. Inaddition, performing aggressive adaptive filtering on these low energydecays actually causes error in estimation in many types of adaptive FIRfilters, e.g. normalized LMS filters, and degrades the overall echocancellation performance.

Infinite impulse response (IIR) filters, or recursive filters, areimplemented forms of pole-zero transfer functions that do not require along tap delay. Typically, IIR filters are used to numerically mimicvery specific echo return paths in which stability of the pole-zerotransfer function can be guaranteed during adaptation. In addition, thepoles must be properly represented numerically and thus practicalembodiments in digital signal processing require a high degree ofprecision in implementation because small bit errors can cause largefilter errors including instability. Methods of adaptation mechanismsare known to those of ordinary skill in the art and are found describedin Adaptive Signal Processing, by Bernard Widrow and Samuel D. Stearns,Prentice-Hall, Inc., Englewood Cliffs, N.J., 1985, particularly pages99-101 and 154-161.

Accordingly, there remains a need for the rapid convergence of an IIRfilter and the stability of an FIR filter to be applied to echocancellation. The present invention, in its several embodiments providesecho cancellation using an adaptive IIR filter and an adaptive FIRfilter.

SUMMARY

The invention, in its several embodiments, provides a method and systemadapted to receive an input signal, to receive a return signal, and toinject into the return signal a corrective signal, which by way ofexemplary application, appreciably cancels echoes in communicationsystems. A first exemplary system includes a return signal conditioningmodule adapted to receive the return signal and output a conditionedreturn signal and an adaptive IIR filter adapted to receive the inputsignal, wherein the adaptive IIR filter is also adapted to receive oneor more gain adjustments from an IIR gain adaptation mechanism thatitself is adapted to receive an IIR filter error signal derived from thedifference of the adaptive IIR filter output and the conditioned returnsignal. The first exemplary embodiments also includes an adaptive FIRfilter that is adapted to receive the input signal, wherein the adaptiveFIR filter is also adapted to receive one or more gain adjustments fromits FIR gain adaptation mechanism that itself is adapted to receive aFIR filter error signal that is preferably derived from the differenceof the adaptive FIR filter output and the conditioned return signal. Inaddition, the first exemplary embodiment includes a selector, orselector subsystem or selection module, that is adapted to receive theIIR filter error signal and the FIR filter error signal and adapted toselect the corrective signal from the FIR filter output and the IIRfilter output preferably based one or more derived performance measures.The exemplary first embodiment may include one or more adaptive IIRfilters and one or more adaptive FIR filters from which the correctivesignal selection is made.

A second exemplary system includes: a nonlinear processing moduleadapted to receive the return signal and output a conditioned returnsignal and an adaptive IIR filter that is adapted to receive the inputsignal, wherein the adaptive IIR filter is also adapted to receive oneor more gain adjustments from its IIR gain adaptation mechanism thatitself is adapted to receive an IIR filter error signal derived from thedifference of the adaptive IIR filter output and the conditioned returnsignal. The second exemplary system embodiment also includes an adaptiveFIR filter that is adapted to receive the input signal and output thecorrective signal, wherein the adaptive FIR filter is also adapted toreceive one or more gain adjustments from its FIR filter gain adaptationmechanism that itself is adapted to receive a FIR filter error signalthat is preferably derived from the difference of the corrective signaland a signal preferably selected from either the adaptive FIR filteroutput and the conditioned return signal preferably based one or morederived performance measures.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and notlimitation in the figures of the accompanying drawings, and in which:

FIG. 1 is a functional block diagram of the prior art;

FIG. 2 is a functional block diagram of an exemplary embodiment of thepresent invention; and

FIG. 3 is a functional block diagram of another exemplary embodiment ofthe present invention.

DETAILED DESCRIPTION OF THE INVENTION

Adaptive IIR filters have been long prevalent in modeling acousticsignals, particularly due to their effectiveness in mimicking specificdecaying behavior. The use of one or more adaptive IIR filters in echocanceling applications, to the exclusion of other filter structures, isnot done due to the wide varying range of conditions in the common echoreturn paths. Nevertheless, these filters offer many advantages that aredesired in echo cancellation when combined with adaptive FIR filters.

FIG. 2 illustrates an exemplary embodiment of the present invention asan echo canceling device 200 where the input signal 110, x_(k) is sentboth to an adaptive IIR filter 210, F_(k)(z), and an adaptive FIR filter220, G_(k)(z). The adaptive FIR filter 220, G_(k)(z), may be representedas the a sum of L taps weighted by adjustable weights or one or moredelay states each having a feed-forward gains, g_(n), for n=0, 1, 2, . .. L. For example, at each time step, k, and for L+1 coefficients, theadaptive FIR filter 220, G_(k)(z), may be represented as:

$\begin{matrix}{{G_{k}(z)} = {\sum\limits_{n = 0}^{L}{g_{n,k} \cdot {z^{- n}.}}}} & \lbrack 3\rbrack\end{matrix}$

The adaptive IIR filter may be represented with poles and zeros orfeed-forward gains, b_(n), for n=0, 1, 2, . . . L, and feedback gains,a_(n), for n=1, 2, . . . L. For example, at each time step, k, and forL+1 feed-forward coefficients and L feedback coefficients, the adaptiveIIR filter 210, F_(k)(z), may be represented as:

$\begin{matrix}{{F_{k}(z)} = {\frac{\sum\limits_{n = 0}^{L}{b_{n,k} \cdot z^{- n}}}{1 + {\sum\limits_{n = 1}^{L}{a_{n,k} \cdot z^{- n}}}}.}} & \lbrack 4\rbrack\end{matrix}$

While one adaptive FIR filter and one adaptive IIR filter have beenillustrated by example in FIG. 2, the present embodiment is readilyextendable to more than one adaptive FIR filter having an adaptationmechanism and more than one adaptive IIR filter having an adaptationmechanism.

Both adaptive filters 210, 220 have coefficients that may be adjusted,or adapted, during the course of the operation of the echo cancelingdevice 200. The return signal 132 is sent through nonlinear processing(NLP) module 230 for conditioning with the NLP module preferablyexecuting functions including line noise filtering and a double talkthreshold testing. The output of the adaptive IIR filter 212 issubtracted from the conditioned return signal 232 and provided as an IIRfilter error signal 214, e_(F) _(k) , to the adaptive IIR filteradaptation mechanism 216. Similarly, the adaptive FIR filter 220generates an output signal 222 using the far end input signal 110 asinput. The adaptive FIR filter output 212 is subtracted from theconditioned return signal 232 and provided as an FIR filter error signal224, e_(G) _(k) , to the adaptive FIR filter adaptation mechanism 226.Preferably, the IIR error signal 214, e_(F) _(k) , is used to assess thereal time performance of the FIR filter and the FIR error signal 224,e_(G) _(k) , is used to assess the real time performance of the IIRfilter. The derived performance measures are preferably used to select,from the outputs of the adaptive filters, a signal to inject into thereturn signal path in order to cancel the echo.

Derived performance measures may also require the return signal. TheEcho Return Loss Enhancement (ERLE) is typically defined as the amountof echo signal reduction between the echo signal, e.g., y_(k), and theerror signal, e_(k)=y_(k)−ŷ_(k). So, for example, the ERLE(dB) may becalculated for K time steps according to:

$\begin{matrix}{{{ERLE}({dB})} = {10\mspace{11mu}{{\log\left( \frac{E\left\lbrack {y^{2}(k)} \right\rbrack}{E\left\lbrack {e^{2}(k)} \right\rbrack} \right)}.}}} & \lbrack 5\rbrack\end{matrix}$

Poor reductions in the error signal tend to indicate poor fits to theecho signal and may indicate where a filter is behaving erratically, andfor the IIR filters, may be working with an unstable set ofcoefficients.

Other performance measures that may establish a performance-basedselection rule include the magnitude of filter coefficient adjustmentsover time steps. For example, an indication of an unstable adaptationmechanism may be discerned from the time history of the adjustedcoefficients indicating variations inconsistent with settling into abest fit.

On a performance basis, such as, but not limited to, the ERLE, the IIRfilter output 212 or the FIR filter output 222 is selected and used asthe echo signal estimate ŷ_(k) 262, which is presumed the signal havingthe best estimate of the echo signal 122, y_(k), (FIG. 1) andaccordingly subtracted from the return signal 132 to yield the near-endinput signal estimate 270, {circumflex over (r)}_(k). The IIR errorsignal 214, e_(F) _(k) , may be used to assess and detect the state ofthe IIR filter 210 stability, by for example the mean squared erroralgorithm. Should instability of the adaptive IIR filter 210 bedetected, the switch 260 is preferably thrown to select the FIR filteroutput 222 as the echo signal estimate ŷ_(k) 262. With the selection ofthe FIR filter output 222, the IIR filter is preferably reset and mayuse a new set of gains selected from a matrix having initial gain setsstored in constituent vectors and the IIR adaptation step size may beadjusted. Additional noise filtering may be applied to the estimatedinput signal as well preferably prior to sending the estimated inputsignal 270, {circumflex over (r)}_(k). to the far end.

Preferably, the FIR adaptation mechanism 226 may also be used todetermine the stability of the adaptive IIR filter 210 and itsadaptation mechanism 216. For example, the stability detector 240 maycontinually monitor 248 the relative changes in the filter coefficientsof the adaptive FIR filter and its ERLE to determine that the FIRadaptation mechanism 226 has become stable or otherwise self-adjustingin very small and consistent steps. Concurrently, the stability detector240 is preferably provided the relative changes 246 in the IIR filtergain coefficient values. If the IIR adaptation mechanism 216 is updatingits coefficients wildly and producing varying ERLE while the adaptationmechanism of the FIR 226 has settled into a set of gain valuesconsistent over time, the adaptive IIR filter is preferably reset. Thestability detector 240 may use ERLE and or other performance measures toassess a preferred filter output as the corrective signal 262 tosubtract form, or inject into, the return signal 132. The stabilitydetector 240 may be included in a switching mechanism, or selectorsubsystem or selector, to effect the selection of the corrective signalor the switching mechanism may be a separate module 260.

Preferably, the selection of one of the outputs 212, 222 of the adaptivefilters 210, 220, F_(k)(z) and G_(k)(z), is tied 244 to an increase inthe step size, or β, or the value of the adapting gain, in theadaptation mechanism of the unselected filter and is also preferablytied 244 to a decrease in the step size, β, or adapting gain value, inthe adaptation mechanism of the selected filter. These step sizes arepreferably stored in a table of adapting gains 250. Accordingly, a newadapting gain for the adaptive FIR adaptation mechanism 254 and a newadapting gain for the adaptive IIR adaptation mechanism 252 may beprovided should a selection 242 be sent to throw the switch 260.

The adaptive FIR filter adaptation mechanism 226 preferably has a set ofinitial gains. The gains may stored in a table 250 as a vector of gainswhere a matrix of these gain vectors may provide for the selection ofmore than one initial set of filter gains. The initial set of gains maybe adjusted at each time step according to an adaptation process. Forexample, each FIR filter coefficient may increased or decreased byadding to the last coefficient value the product of the step size, β,the error signal, e_(G) _(k) , the normalized far-end input signal,X_(k)/X_(max). In addition, the adaptation mechanism 226 may be haltedor the step size reduced temporarily should the double talk thresholdtest on the return signal 132, r_(k)+y_(k) detect a double talk state(DT_(k)) 234.

The adaptive IIR filter adaptation mechanism 216 also preferably has aset of initial gains. As with the adaptive FIR filter 220, the gains maystored as a vector of gains where a matrix of these gain vectors mayprovide for the selection of more than one initial set of filter gainsfrom a table 250. The initial set of gains may be adjusted at each timestep according to an adaptation process. Algorithms for recursiveadaptive filters preferably include the LMS algorithms, hyperstableadaptive recursive filter algorithms, and sequential regressionalgorithms. For a minimal number of executions, the LMS algorithms arepresently preferred. In addition, the adaptation mechanism of the IIRmay be halted or the step size reduced temporarily should the thresholdtest on the return signal, r_(k)+y_(k) detect a double talk state(DT_(k)) 234.

FIG. 3 illustrates an exemplary functional block diagram of analternative embodiment 300 of the present invention. In this example,the far-end input signal 110, X_(k), is provided to both the adaptiveFIR 320, G_(k)(z), and the adaptive IIR 310, F_(k)(z). The output of theadaptive FIR filter 322, ŷ_(k), is presumed the best estimate of theecho signal 122 and subtracted from the return signal 132, r_(k)+y_(k),to yield the estimated input signal 370, {circumflex over (r)}_(k).Additional noise filtering may be applied to the estimated input signal370 as well prior to sending the estimated input signal to the far end.

The return signal 132 having both the near-end input signal, r_(k) andan echo signal, y_(k), is provided to a nonlinear processing module 330for conditioning where the return signal 132 is preferably filtered fornoise and a double talk threshold test is preferably applied. The outputof the adaptive IIR filter 312 is subtracted from the conditioned returnsignal 332 yielding the IIR filter error signal 312, e_(F) _(k) , wherethe IIR filter error signal in turn drives, in part, the IIR adaptationmechanism 316. Preferably the IIR mechanism 316 uses an LMS algorithmtaking in the far-end input signal 110, X_(k), and the IIR filter errorsignal 312, e_(F) _(k) , and other adaptation algorithms for recursivefilters may be used instead or in combination such as for examplehyperstable adaptive recursive filter algorithms and sequentialregression algorithms. By this adaptive IIR filter stage 302, the echocanceller 300 prepares the adaptive IIR filter 310 as an echo modelreference for the adaptive FIR filter 320. Accordingly, more than oneadaptive IIR filter may be used where the selection of the reference forthe adaptive FIR filter 320 is based on determined performancecharacteristics of all of the adaptive IIR filters.

The adaptive IIR filter output 312 is subtracted from the FIR filteroutput 322 yielding the FIR filter error signal 324, e_(G) _(k) , wherethis FIR filter error signal 322 in turn drives, in part, the FIRadaptation mechanism 326. The FIR adaptation mechanism 326 preferablyuses an LMS algorithm taking in the far-end input signal 110, X_(k), andthe FIR filter error signal 324, e_(G) _(k) , as described above andother adaptation algorithm may be used instead or in combination. Theadapting gains, or step sizes, β, of the FIR adaptation mechanism 326are preferably drawn 352 from a table 350 where larger adapting gainsmay be used for the FIR adaptation mechanism 326 when the adaptive IIRfilter 310 is used as the echo reference to aggressively drive theadaptive FIR 320 to converge, that is to drive the FIR filter errorsignal 324, e_(G) _(k) , to zero. Accordingly, a stability detectingmodule 340 is preferably used to monitor the IIR filter error signal312, e_(F) _(k) , and monitor 344 the adjustments to the IIR filtergains as generated by the IIR adaptation mechanism 316. Once thestability detecting module has determined the IIR filter 310 isprocessing in a stable fashion typically driving the IIR filter errorsignal 314, e_(F) _(k) , to or near zero and consistently sustainingthis level. Preferably based on the determinations 342 of stabilitydetecting module 340, the step sizes for the FIR adaptation mechanism326 preferably provided by the adapting gains table 350 may be increased352 and the step sizes for the IIR adaptation mechanism 315 preferablyprovided by the adapting gains table 350 may be increased 354 may bedecreased.

Preferably based on a double talk state (DT_(k)) 334 provided by anonlinear processing module 330 having double talk threshold-baseddetection, both the IIR adaptation mechanism 316 and the FIR adaptationmechanism 326 preferably reduce or halt their respective adaptationmechanisms should a double talk state 334 be signaled by the nonlinearprocessing module 330. In addition, the IIR error signal 314, e_(F) _(k), is preferably monitored for stability using for example the meansquared error compared with a stability threshold. In addition,continued large adjustments of the IIR gains may be provided 344 to thestability detection module 344 by the IIR adaptation mechanism 316 fordetermining the stability of the IIR adaptation mechanism. A selectorsubsystem may include both the stability detection module 430 and aswitch 360 or the selector subsystem may be distributed within thesystem. If the instability threshold is achieved, the stabilitydetection module 340 preferably signals 342 the switch 360 so the outputof the FIR filter 322 is subtracted from the conditioned return signal332 and the IIR gains are reset and may be supplied a new set of gainsthat are selected from a matrix having gains represented in vectors.Once the IIR is reset, the switch 360 may reset to derive the FIR errorsignal from the IIR output. In addition, the IIR adapting gain may beselected from a table 350 having values lower in step size than thatpreviously used in the unstable event.

The words used in this specification to describe the invention and itsvarious embodiments are to be understood not only in the sense of theircommonly defined meanings, but to include by special definition in thisspecification structure, material or acts beyond the scope of thecommonly defined meanings. Thus if an element can be understood in thecontext of this specification as including more than one meaning, thenits use in a claim must be understood as being generic to all possiblemeanings supported by the specification and by the word itself.

Many alterations and modifications may be made by those having ordinaryskill in the art without departing from the spirit and scope of theinvention and its several embodiments disclosed herein. Therefore, itmust be understood that the illustrated embodiments have been set forthonly for the purposes of example and that it should not be taken aslimiting the invention as defined by the following claims.

1. A method comprising: generating a first infinite impulse response(IIR) error signal by differencing a conditioned return signal and aninput signal filtered by a first adaptive IIR filter wherein the firstadaptive IIR filter comprises at least one feed-forward gain and atleast one feedback gain adapted to be adjusted via a first IIRadaptation mechanism and wherein the first IIR adaptation mechanism isadapted to receive the generated first IIR error signal; selecting asignal from a group of signals comprising the input signal filtered bythe first adaptive IIR filter and the conditioned return signal; andgenerating a finite-impulse response (FIR) error signal by differencingthe selected signal and an input signal filtered by an adaptive FIRfilter, wherein the adaptive FIR filter comprises at least onefeed-forward gain adapted to be adjusted via a FIR adaptation mechanismand wherein the FIR adaptation mechanism is adapted to receive thegenerated FIR error signal; using the IIR error signal to assess anddetect a stability state of the first adaptive IIR filter and when aninstability of the first adaptive IIR filter is detected, selecting anoutput of the adaptive FIR filter as an echo signal estimate andresetting the first adaptive IIR filter.
 2. The method as claimed inclaim 1 further comprising the step of subtracting the input signalfiltered by the adaptive FIR filter from a return signal.
 3. The methodas claimed in claim 1 wherein the selecting of the signal from a groupof signals comprising the input signal filtered by the first adaptiveIIR filter and the conditioned return signal is based on the generatedfirst IIR error signal.
 4. The method as claimed in claim 1 wherein theselecting of the signal from a group of signals comprising the inputsignal filtered by the first adaptive IIR filter and the conditionedreturn signal is based on magnitudes of first IIR filter gainadjustments over a period of time.
 5. The method as claimed in claim 1wherein the conditioned return signal is a return signal subjected tonoise filtering.
 6. The method as claimed in claim 1 wherein theconditioned return signal is a return signal tested to determine adouble talk state.
 7. The method as claimed in claim 1 wherein the firstIIR adaptation mechanism and the FIR adaptation mechanism is adapted toreceive the determined double talk state.
 8. The method as claimed inclaim 1 further comprising: generating a second IIR error signal bydifferencing a conditioned return signal and an input signal filtered bya second adaptive IIR filter wherein the second adaptive IIR filtercomprises at least one feed-forward gain and at least one feedback gainadapted to be adjusted via a second IIR adaptation mechanism and whereinthe second IIR adaptation mechanism is adapted to receive the generatedsecond IIR error signal; and wherein the group of signals from which theselected signal is selected further comprises the second adaptive IIRfilter output.
 9. A system adapted to receive an input signal, toreceive a return signal, and to inject into the return signal acorrective signal, the system comprising: a nonlinear processing moduleadapted to receive the return signal and output a conditioned returnsignal; a first adaptive infinite impulse response (IIR) filter adaptedto receive the input signal, wherein the first adaptive FIR filter isfarther adapted to receive one or more gain adjustments from a first IIRgain adaptation mechanism, and wherein the first IIR gain adaptationmechanism is adapted to receive a first IIR filter error signal derivedfrom the difference of an output of the first adaptive IIR filter andthe conditioned return signal; and an adaptive finite-impulse response(FIR) filter adapted to receive the input signal and output thecorrective signal, wherein the adaptive FIR filter is further adapted toreceive one or more gain adjustments from a FIR gain adaptationmechanism, and wherein the FIR gain adaptation mechanism is adapted toreceive a FIR filter error signal derived from the difference of thecorrective signal and a signal selected from a group of signalscomprising the output of the first adaptive IIR filter and theconditioned return signal; wherein the IIR error signal assess anddetects a stability state of the first adaptive IIR filter and when aninstability of the first adaptive IIR filter is detected, an output ofthe adaptive FIR filter is selected as an echo signal estimate and thefirst adaptive IIR filter is reset.
 10. The system as claimed in claim 9wherein the nonlinear processing module is further adapted to determineand output a state of double talk; and wherein the first IIR adaptationmechanism is further adapted to receive the double talk state indicatorand effect a change in an IIR adapting gain based on the received doubletalk state indicator; and wherein the first FIR adaptation mechanism isfurther adapted to receive the double talk state indicator and effect achange in an FIR adapting gain based on the received double talk stateindicator.
 11. The system as claimed in claim 10 wherein the nonlinearprocessing module is further adapted to condition the return signal bynoise filtering.
 12. The system as claimed in claim 9 wherein the firstFIR adaptation mechanism has at least one first FIR adapting gain, orfirst FIR gain adjustment step size, that is dependent on the selectionof the signal with which the corrective signal is differenced andwherein the first IIR adaptation mechanism has at least one first IIRadapting gain, or first IIR gain adjustment step size, that is dependenton the selection of the corrective signal.
 13. The system as claimed inclaim 12 further comprising a selector subsystem adapted to determinethe selection from the group of signals comprising the output of thefirst adaptive IIR filter and the conditioned return signal based on aderived performance measure.
 14. The system as claimed in claim 12wherein the selector subsystem is further adapted to receive the firstIIR filter error signal.
 15. The system as claimed in claim 12 whereinthe selector subsystem is further adapted to receive a plurality ofmagnitudes of first IIR filter gain adjustments over a period of timeand a plurality of magnitudes of FIR filter gain adjustments over aperiod of time.
 16. The system as claimed in claim 12 wherein theselector subsystem is further adapted to receive a plurality ofmagnitudes of first IIR filter gains over a period of time and aplurality of magnitudes of FIR filter gains over a period of time. 17.The system as claimed in claim 9 further comprising a second adaptiveIIR filter adapted to receive the input signal, wherein the secondadaptive IIR filter is further adapted to receive one or more gainadjustments from a second IIR gain adaptation mechanism, and wherein thesecond IIR gain adaptation mechanism is adapted to receive a second IIRfilter error signal derived from the difference of an output of thesecond adaptive IIR filter and the conditioned return signal; andwherein the group of signals from which the selected signal is selectedfurther comprises the second adaptive IIR filter.